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The power of knowledge: unraveling the influence of knowledge characteristics on inter-firm patent transfers.

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Authors: Ma, Ding1 (AUTHOR) mading@whut.edu.cn, Cai, Zhishan2 (AUTHOR) caizhishan@cqu.edu.cn
Source: Journal of Technology Transfer. Jun2026, Vol. 51 Issue 3, p1820-1851. 32p.
Subject Terms: *Intellectual property, *Electric vehicle industry, Knowledge transfer, Random graphs
Geographic Terms: China
Abstract: Inter-firm patent transfers dominate overall patent transactions, yet relevant research remains limited, particularly regarding the essence of patent transfers, i.e., knowledge flow. This study provides a pilot exploration of the impact of firms' multidimensional knowledge characteristics on inter-firm patent transfers, distinguishing between different industry stages and firm roles as suppliers or recipients. Knowledge characteristics are classified into the structural features of firms' knowledge elements (degree and betweenness centrality) and the attributes of firms' knowledge stock (scale and diversity). Using patent data from China's new energy vehicle industry (2012–2021), we constructed patent transfer and knowledge combination networks to quantify these characteristics and applied exponential random graph models (ERGM) to analyze their stage-specific effects on firms' tendencies to transfer or acquire patents. The results reveal differential impacts across industry stages. In the initial stage, firms with intermediary knowledge elements tend to engage in patent transfer. The degree centrality of firm's knowledge elements negatively impacts firms' patent transfer propensity, while knowledge diversity inhibits firms from acquiring patents. In the development stage, the scale of knowledge stock increase patent transfer likelihood whereas betweenness centrality of firm's knowledge elements demonstrates inhibitory effects. Firms possessing high-degree centrality knowledge elements prefer to provide patents, while firms with diverse knowledge elements are inclined to acquire patents. This study offers insights for firms to optimize resource allocation and for policymakers to enhance the vitality of patent transfer markets. [ABSTRACT FROM AUTHOR]
Database: Entrepreneurial Studies Source
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: <searchLink fieldCode="AR" term="%22Ma%2C+Ding%22">Ma, Ding</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mading@whut.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Cai%2C+Zhishan%22">Cai, Zhishan</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> caizhishan@cqu.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Technology+Transfer%22">Journal of Technology Transfer</searchLink>. Jun2026, Vol. 51 Issue 3, p1820-1851. 32p.
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  Data: *<searchLink fieldCode="DE" term="%22Intellectual+property%22">Intellectual property</searchLink><br />*<searchLink fieldCode="DE" term="%22Electric+vehicle+industry%22">Electric vehicle industry</searchLink><br /><searchLink fieldCode="DE" term="%22Knowledge+transfer%22">Knowledge transfer</searchLink><br /><searchLink fieldCode="DE" term="%22Random+graphs%22">Random graphs</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Inter-firm patent transfers dominate overall patent transactions, yet relevant research remains limited, particularly regarding the essence of patent transfers, i.e., knowledge flow. This study provides a pilot exploration of the impact of firms' multidimensional knowledge characteristics on inter-firm patent transfers, distinguishing between different industry stages and firm roles as suppliers or recipients. Knowledge characteristics are classified into the structural features of firms' knowledge elements (degree and betweenness centrality) and the attributes of firms' knowledge stock (scale and diversity). Using patent data from China's new energy vehicle industry (2012–2021), we constructed patent transfer and knowledge combination networks to quantify these characteristics and applied exponential random graph models (ERGM) to analyze their stage-specific effects on firms' tendencies to transfer or acquire patents. The results reveal differential impacts across industry stages. In the initial stage, firms with intermediary knowledge elements tend to engage in patent transfer. The degree centrality of firm's knowledge elements negatively impacts firms' patent transfer propensity, while knowledge diversity inhibits firms from acquiring patents. In the development stage, the scale of knowledge stock increase patent transfer likelihood whereas betweenness centrality of firm's knowledge elements demonstrates inhibitory effects. Firms possessing high-degree centrality knowledge elements prefer to provide patents, while firms with diverse knowledge elements are inclined to acquire patents. This study offers insights for firms to optimize resource allocation and for policymakers to enhance the vitality of patent transfer markets. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1007/s10961-025-10248-0
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 32
        StartPage: 1820
    Subjects:
      – SubjectFull: Intellectual property
        Type: general
      – SubjectFull: Electric vehicle industry
        Type: general
      – SubjectFull: Knowledge transfer
        Type: general
      – SubjectFull: Random graphs
        Type: general
      – SubjectFull: China
        Type: general
    Titles:
      – TitleFull: The power of knowledge: unraveling the influence of knowledge characteristics on inter-firm patent transfers.
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            NameFull: Ma, Ding
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            NameFull: Cai, Zhishan
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            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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              Value: 51
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            – TitleFull: Journal of Technology Transfer
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